class_docstr: Base class for EncoderDecoder tests. Tests for specific classes should
  inherit from this and tf.test.TestCase.
docstr: Creates example data for a test
docstr_tok: ["Creates","example","data","for","a","test"]
code: def _create_example(self):
      """Creates example data for a test"""
      source = np.random.randn(
          self.batch_size, self.sequence_length, self.input_depth
      )
      source_len = np.random.randint(
          0, self.sequence_length, [self.batch_size]
      )
      target_len = np.random.randint(
          0, self.sequence_length * 2, [self.batch_size]
      )
      target = np.random.randn(
          self.batch_size, np.max(target_len), self.input_depth
      )
      labels = np.random.randint(
          0, self.vocab_size, [self.batch_size, np.max(target_len) - 1]
      )
  
      example_ = namedtuple(
          "Example",
          ["source", "source_len", "target", "target_len", "labels"],
      )
      return example_(source, source_len, target, target_len, labels)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from collections import namedtuple
  import yaml
  import numpy
  import tensorflow
  from seq2seq.data import vocab, input_pipeline
  from seq2seq.training import utils
  from seq2seq.test import utils
  from seq2seq.models import BasicSeq2Seq, AttentionSeq2Seq
label_desc: Use image node_id 4 for calling the EncoderDecoderTests obj's underlying member method code with example usage: obj._create_example() and returns: example_